摘要
为提升物流配送效率,降低配送成本,提出一种改进麻雀搜索算法M-SSA求解物流配送中心选址问题。在基本麻雀搜索算法SSA中,设计均匀化Logistic映射机制提升初始种群的均匀性和随机性;利用正余弦优化和惯性权重机制改进发现者位置更新,提升全局搜索能力;引入柯西混沌变异机制增强种群多样性,避免局部最优解。利用M-SSA算法求解物流配送中心选址问题。实验结果表明,在解决配送中心选址问题上,M-SSA算法可以降低物流配送成本,提升配送效率。
To improve logistics distribution efficiency and reduce the distribution costs,an improved sparrow search algorithm M-SSA was put forward to solve logistics distribution center location problem.In basic sparrow search algorithm,a homogenization Logistic chaotic mapping mechanism was designed to improve the uniformity and randomness of initial population.The Sine Cosine optimization and inertia weight mechanism were used to improve the location update of discoverers,and promote the global searching ability.The Cauchy chaos mutation mechanism was introduced to ascend the population diversity to avoid the optimal solution.M-SSA was used to solve logistics distribution center location problem.The results show that the M-SSA algorithm can reduce distribution costs and improve the efficiency of distribution when dealing with the distribution center location selection problem.
作者
杨小琴
朱玉全
YANG Xiao-qin;ZHU Yu-quan(School of Computer and Information Engineering,Pujiang Institute of Nanjing Technology University,Nanjing 211134,China;School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013,China)
出处
《计算机工程与设计》
北大核心
2023年第5期1441-1450,共10页
Computer Engineering and Design
基金
江苏省现代教育技术研究课题基金项目(2019-R-81745)
江苏省高校哲学社会科学研究一般基金项目(2019SJA2068)。
关键词
配送中心选址
麻雀搜索算法
正余弦优化
柯西混沌变异
均匀化Logistic映射
配送效率
种群多样性
distribution center location
sparrow search algorithm
sine cosine optimization
Cauchy chaos mutation
homogenization Logistics mapping
distribution efficiency
population diversity
